This course will focus on the analysis of categorical dependent variables,
commonly found in criminal justice research. We will also spend some time
at the end of the semester on special types of regression models (i.e., survival
models, hierarchical models). We will focus on analytical techniques, software
applications, and policy relevance for categorical research.

The prerequisite for this course is successful completion of CJ906 (Advanced
Quantitative Methods in Criminal Justice Data Research) or an equivalent course.

Requirements:

Your semester grade will consist of two technical papers and one review
paper (each worth 20% of your grade), and one final paper and presentation
(40% of your grade). The technical papers will each utilize a special technique
learned in the course (binary, nominal, ordinal, and count models).
Students should be able to discuss their rationale for analysis, and any special
technical issues surrounding the analysis. The third paper will be
a review of your peers' second technical paper.

The final paper will be presented to the class, and should focus on a
categorical dependent variable and the correct methods for analysis. Relevant
criminal justice implications should be discussed, as well as directions
for future research. This paper is expected to be of publication quality,
and students will be encouraged to submit these papers for publication.

Students must supply their own data sets for this course. Data are readily
available on-line from the Inter-University Consortium for Political and Social
Research (http://www.icpsr.umich.edu/).
Data from a Master's thesis may also be used. I strongly recommend
that you acquire a dataset before the first day of class. Appropriate
data sets will have either (1) a relevant continuous dependent variable that
can be easily recoded into categories for analysis, or (2) a choice of several
different dependent variables that can be used with different methods (ie,
binary, multinomial, count, truncated or censored). Option #2 is preferred,
since analysis using count data is an integral part of the course, and those
variables typically cannot be created from continuous variables.

Software:

Students may choose to use either LIMDEP or SAS to complete the analysis
in their papers. Unfortunately, SPSS is not able to analyze categorical
dependent variables.

Optional:
Greene, William H. (1995). LIMDEP Version 7.0 User's Manual. Plainview,
NY: Econometric Software. This manual is not mandatory for the course, because much of it is available
with the software and on-line at http://www.limdep.com.

Norusis, M. J. (2000). SPSS 10.0 Guide to Data Analysis. Englewood
Cliffs, NJ: Prentice-Hall. A self-directed guide to using SPSS version 8.0. Students who have never
used SPSS before, or who need a helpful guide should buy this book. May not
be helpful for students already familiar with SPSS.